Search results for: Auto Regressive (AR) Coefficients

Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

Abstract:

In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.

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Authors: Saeed jalilzadeh, Mohammad Reza Safari Tirtashi, Mohsen Sadeghi

Abstract:

this paper focuses on designing of PSS and SVC controller based on chaos and PSO algorithms to improve the stability of power system. Single machine infinite bus (SMIB) system with SVC located at the terminal of generator has been considered to evaluate the proposed controllers where both SVC and PSS have the same controller. The coefficients of PSS and SVC controller have been optimized by chaos and PSO algorithms. Finally the system with proposed controllers has been simulated for the special disturbance in input power of generator, and then the dynamic responses of generator have been presented. The simulation results showed that the system composed with recommended controller has outstanding operation in fast damping of oscillations of power system.

Keywords: PSS, CHAOS, PSO, Stability

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Authors: Nebi Gedik

Abstract:

The aim of the brain-computer interface studies on electroencephalogram (EEG) signals containing motor imagery is to extract the effective features that will provide the highest possible classification accuracy for the detection of the desired motor movement. However, achieving this goal is difficult as the most suitable frequency band and time frame vary from subject to subject. In this study, the classification success of the two-feature data obtained from raw EEG signals and the coefficients of the multi-resolution analysis method applied to the EEG signals were analyzed comparatively. The method was applied to several EEG channels (C3, Cz and C4) signals obtained from the EEG data set belonging to the publicly available BCI competition III.

Keywords: Motor imagery, EEG, wave atom transform, k-NN.

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Authors: Miloud Frikel , Boubekeur Targui, Francois Hamon, Mohammed M'SAAD

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In this paper we propose an enhanced equalization technique for multi-carrier code division multiple access (MC-CDMA). This method is based on the control of Equal Gain Combining (EGC) technique. Indeed, we introduce a new level changer to the EGC equalizer in order to adapt the equalization parameters to the channel coefficients. The optimal equalization level is, first, determined by channel training. The new approach reduces drastically the mutliuser interferences caused by interferes, without increasing the noise power. To compare the performances of the proposed equalizer, the theoretical analysis and numerical performances are given.

Keywords: MC-CDMA, Equalization, EGC, Single User Detection.

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Authors: Agnieszka Misztal

Abstract:

The popularity of quality management system models continues to grow despite the transitional crisis in 2008. Their development is associated with demands of the new requirements for entrepreneurs, such as risk analysis projects and more emphasis on supervision of outsourced processes. In parallel, it is appropriate to focus attention on the selection of companies aspiring to a quality management system. This is particularly important in the automotive supplier industry, where requirements transferred to the levels in the supply chain should be clear, transparent and fairly satisfied. The author has carried out a series of researches aimed at finding the factors that allow for the effective implementation of the quality management system in automotive companies. The research was focused on four groups of companies: 1) manufacturing (parts and assemblies for the purpose of sale or for vehicle manufacturers), 2) service (repair and maintenance of the car) 3) services for the transport of goods or people, 4) commercial (auto parts and vehicles). The identified determinants were divided into two types of criteria: internal and external, as well as hard and soft. The article presents the hard – technical factors that an automotive company must meet in order to achieve the goal of the quality management system implementation.

Keywords: Automotive industry, quality management system.

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Authors: J. Kala, J. Melcher, M. Škaloud, Z. Kala

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In the paper, the results of sensitivity analysis of the influence of initial imperfections on the web stress state of a thinwalled girder are presented. The results of the study corroborate a very good and effective agreement of experiments with theory. Most input random quantities were found experimentally. The change of sensitivity coefficients in dependence on working load value is analysed. The stress was analysed by means of a geometrically and materially non-linear solution by applying the program ANSYS. This research study offers important background for theoretical studies of stability problems, post-critical effects and limit states of thin-walled steel structures.

Keywords: Buckling, Fatigue, Imperfection, Steel, Sensitivity analysis.

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Authors: Meysam Mohamad pour, Fardad Farokhi

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In this paper in consideration of each available techniques deficiencies for speech recognition, an advanced method is presented that-s able to classify speech signals with the high accuracy (98%) at the minimum time. In the presented method, first, the recorded signal is preprocessed that this section includes denoising with Mels Frequency Cepstral Analysis and feature extraction using discrete wavelet transform (DWT) coefficients; Then these features are fed to Multilayer Perceptron (MLP) network for classification. Finally, after training of neural network effective features are selected with UTA algorithm.

Keywords: Multilayer perceptron (MLP) neural network, Discrete Wavelet Transform (DWT) , Mels Scale Frequency Filter , UTA algorithm.

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Authors: Serge B. Provost, Min Jiang

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The density estimates considered in this paper comprise a base density and an adjustment component consisting of a linear combination of orthogonal polynomials. It is shown that, in the context of density approximation, the coefficients of the linear combination can be determined either from a moment-matching technique or a weighted least-squares approach. A kernel representation of the corresponding density estimates is obtained. Additionally, two refinements of the Kronmal-Tarter stopping criterion are proposed for determining the degree of the polynomial adjustment. By way of illustration, the density estimation methodology advocated herein is applied to two data sets.

Keywords: kernel density estimation, orthogonal polynomials, moment-based methodologies, density approximation.

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Authors: Boris Barbolyas, Kristina Buckova, Tomas Volensky, Cyril Belavy, Ladislav Dedik

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Background: Based on statokinezigram, the human balance control is often studied. Approach to human postural reaction analysis is based on a combination of stabilometry output signal with retroreflective marker data signal processing, analysis, and understanding, in this study. The study shows another original application of Method of Developed Statokinesigram Trajectory (MDST), too. Methods: In this study, the participants maintained quiet bipedal standing for 10 s on stabilometry platform. Consequently, bilateral vibration stimuli to Achilles tendons in 20 s interval was applied. Vibration stimuli caused that human postural system took the new pseudo-steady state. Vibration frequencies were 20, 60 and 80 Hz. Participant's body segments - head, shoulders, hips, knees, ankles and little fingers were marked by 12 retroreflective markers. Markers positions were scanned by six cameras system BTS SMART DX. Registration of their postural reaction lasted 60 s. Sampling frequency was 100 Hz. For measured data processing were used Method of Developed Statokinesigram Trajectory. Regression analysis of developed statokinesigram trajectory (DST) data and retroreflective marker developed trajectory (DMT) data were used to find out which marker trajectories most correlate with stabilometry platform output signals. Scaling coefficients (λ) between DST and DMT by linear regression analysis were evaluated, too. Results: Scaling coefficients for marker trajectories were identified for all body segments. Head markers trajectories reached maximal value and ankle markers trajectories had a minimal value of scaling coefficient. Hips, knees and ankles markers were approximately symmetrical in the meaning of scaling coefficient. Notable differences of scaling coefficient were detected in head and shoulders markers trajectories which were not symmetrical. The model of postural system behavior was identified by MDST. Conclusion: Value of scaling factor identifies which body segment is predisposed to postural instability. Hypothetically, if statokinesigram represents overall human postural system response to vibration stimuli, then markers data represented particular postural responses. It can be assumed that cumulative sum of particular marker postural responses is equal to statokinesigram.

Keywords: Center of pressure (CoP), a method of developed statokinesigram trajectory (MDST), a model of postural system behavior, retroreflective marker data.

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Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely, where the subspace of the covariance matrix is decomposed to separate the signal subspace from noise subspace. The decomposition is normally done by using either the eigenvalue decomposition (EVD) or the singular value decomposition (SVD) of the auto-correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. This paper considers the estimation of the multipath slow frequency hopping (FH) channel using noise space based method. In particular, an efficient method is proposed to estimate the multipath time delays by applying multiple signal classification (MUSIC) algorithm which is based on the null space extracted by the rank revealing LU (RRLU) factorization. As a result, precise information is provided by the RRLU about the numerical null space and the rank, (i.e., important tool in linear algebra). The simulation results demonstrate the effectiveness of the proposed novel method by approximately decreasing the computational complexity to the half as compared with RRQR methods keeping the same performance.

Keywords: Time Delay Estimation, RRLU, RRQR, MUSIC, LS-ESPRIT, LS-ESPRIT, Frequency Hopping.

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Authors: Keunseok Cho, Sangbae Jeong, Hyungwook Chang, Minsoo Hahn

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In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is proposed. Also, reduced bits are used to enhance sound quality. The performance of the proposed algorithm is evaluated by sound quality and bit reduction rates in clean and frame loss conditions.

Keywords: G.729.1, MDCT coefficient, NLMS, spectral envelope.

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Authors: E.Darzi

Abstract:

In this study, a reformer model simulation to use refinery (Farashband refinery, Iran) waste natural gas. In the petroleum and allied sectors where natural gas is being encountered (in form of associated gas) without prior preparation for its positive use, its combustion (which takes place in flares, an equipment through which they are being disposed) has become a great problem because of its associated environmental problems in form of gaseous emission. The proposed model is used to product syngas from waste natural gas. A detailed steady model described by a set of ordinary differential and algebraic equations was developed to predict the behavior of the overall process. The proposed steady reactor model was validated against process data of a reformer synthesis plant recorded and a good agreement was achieved. H2/CO ratio has important effect on Fischer- Tropsch synthesis reactor product and we try to achieve this parameter with best designing reformer reactor. We study different kind of reformer reactors and then select auto thermal reforming process of natural gas in a fixed bed reformer that adjustment H2/CO ratio with CO2 and H2O injection. Finally a strategy was proposed for prevention of extra natural gas to atmosphere.

Keywords: Fischer-Tropsch, injection, reformer, syngas, waste natural gas.

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Authors: Alireza Bozorgian, Navid Majdi Nasab, Abdolreza Memari

Abstract:

A continuum model is presented to study vdW interaction on buckling analysis of multi-walled walled carbon nanotube. In previous studies, only the vdW interaction between adjacent two layers was considered and the vdW interaction between the other two layers was neglected. The results show that the vdW interaction cofficients are dependent on the change of interlayer spacing and the radii of tubes. With increase of radii the vdW coefficients approach a constant value. The numerical results show that the effect of vdW interaction on the critical strain for a doublewalled CNT is negligible when the radius is large enough for the both the cases of before and after buckling.

Keywords: Buckling, Carbon nanotube, van der Waals interaction, Multi-walled Carbon nanotube, Critical Strain, Prebuckling Pressure

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Authors: R. Manjith, C. Muthukumari

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In this paper, a novel Linear Feedback Shift Register (LFSR) with Look Ahead Clock Gating (LACG) technique is presented to reduce the power consumption in modern processors and System-on-Chip. Clock gating is a predominant technique used to reduce unwanted switching of clock signals. Several clock gating techniques to reduce the dynamic power have been developed, of which LACG is predominant. LACG computes the clock enabling signals of each flip-flop (FF) one cycle ahead of time, based on the present cycle data of the flip-flops on which it depends. It overcomes the timing problems in the existing clock gating methods like datadriven clock gating and Auto-Gated flip-flops (AGFF) by allotting a full clock cycle for the determination of the clock enabling signals. Further to reduce the power consumption in LACG technique, FFs can be grouped so that they share a common clock enabling signal. Simulation results show that the novel grouped LFSR with LACG achieves 15.03% power savings than conventional LFSR with LACG and 44.87% than data-driven clock gating.

Keywords: AGFF, data-driven, LACG, LFSR.

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Authors: Daniel Olmos-Liceaga

Abstract:

Ventricular fibrillation is a very important health problem as is the cause of most of the sudden deaths in the world. Waves of electrical activity are sent by the SA node, propagate through the cardiac tissue and activate the mechanisms of cell contraction, and therefore are responsible to pump blood to the body harmonically. A spiral wave is an abnormal auto sustainable wave that is responsible of certain types of arrhythmias. When these waves break up, give rise to the fibrillation regime, in which there is a complete loss in the coordination of the contraction of the heart muscle. Interaction of spiral waves and obstacles is also of great importance as it is believed that the attachment of a spiral wave to an obstacle can provide with a transition of two different arrhythmias. An obstacle can be partially excitable or non excitable. In this talk, we present a numerical study of the interaction of meandering spiral waves with partially and non excitable obstacles and focus on the problem where the obstacle plays a fundamental role in the switch between different spiral regimes, which represent different arrhythmic regimes. Particularly, we study the phenomenon of destabilization of spiral waves due to the presence of obstacles, a phenomenon not completely understood (This work will appear as a Chapter in a Book named Cardiac Arrhytmias by INTECH under the name "Spiral Waves, Obstacles and Cardiac Arrhythmias", ISBN 979-953-307-050-5.).

Keywords: Arrhythmias, Cardiac tissue, Obstacles, Spiral waves

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Authors: A. M. Sagir

Abstract:

This paper derived four newly schemes which are combined in order to form an accurate and efficient block method for parallel or sequential solution of third order ordinary differential equations of the form y''' = f(x, y, y', y''), y(α)=y₀, y'(α)=β, y''(α)=η with associated initial or boundary conditions. The implementation strategies of the derived method have shown that the block method is found to be consistent, zero stable and hence convergent. The derived schemes were tested on stiff and non – stiff ordinary differential equations, and the numerical results obtained compared favorably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep, Self starting, Third Order Ordinary Differential Equations.

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Authors: Cor M. Rops, Giaco C. Oosterbaan, Cees W.M. v/d Geld

Abstract:

Equipment miniaturisation offers several opportunities such as an increased surface-to-volume ratio and higher heat transfer coefficients. However, moving towards small-diameter channels demands extra attention to fouling, reliability and stable operation of the system. The present investigation explores possibilities to enhance the stability of the once-through micro evaporator by reducing its flow boiling induced pressure fluctuations. Experimental comparison shows that the measured reduction factor approaches a theoretically derived value. Pressure fluctuations are reduced by a factor of ten in the solid conical channel and a factor of 15 in the porous conical channel. This presumably leads to less backflow and therefore to a better flow control.

Keywords: Flow boiling, Operation stability, Microfluidics, Microchannels.

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Authors: M. Venkatesan, N. Shenbaga Vinayaga Moorthi, R. Karthikeyan, A. Manivannan

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Homogeneous Charge Compression (HCCI) Ignition technology has been around for a long time, but has recently received renewed attention and enthusiasm. This paper deals with experimental investigations of HCCI engine using hydrous methanol as a primary fuel and Dimethyl Ether (DME) as an ignition improver. A regular diesel engine has been modified to work as HCCI engine for this investigation. The hydrous methanol is inducted and DME is injected into a single cylinder engine. Hence, hydrous methanol is used with 15% water content in HCCI engine and its performance and emission behavior is documented. The auto-ignition of Methanol is enabled by DME. The quantity of DME varies with respect to the load. In this study, the experiments are conducted independently and the effect of the hydrous methanol on the engine operating limit, heat release rate and exhaust emissions at different load conditions are investigated. The investigation also proves that the Hydrous Methanol with DME operation reduces the oxides of Nitrogen and smoke to an extreme low level which is not possible by the direct injection CI engine. Therefore, it is beneficial to use hydrous methanol-DME HCCI mode while using hydrous methanol in internal Combustion Engines.

Keywords: Hydrous Methanol, Dimethyl ether, Performance, Emission and Combustion.

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Authors: Tamal Bose, Zhurun Zhang, Miloje Radenkovic, Ojas Chauhan

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In this paper, a novel approach is presented for designing multiplier-free state-space digital filters. The multiplier-free design is obtained by finding power-of-2 coefficients and also quantizing the state variables to power-of-2 numbers. Expressions for the noise variance are derived for the quantized state vector and the output of the filter. A “structuretransformation matrix" is incorporated in these expressions. It is shown that quantization effects can be minimized by properly designing the structure-transformation matrix. Simulation results are very promising and illustrate the design algorithm.

Keywords: Digital filters, minimum noise, multiplier-free, quantization, state-space.

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Authors: Mohammad Shanbghazani, Vahid Heidarpour, Iraj Mirzaee

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In this study a two dimensional axisymmetric, steady state and incompressible laminar flow in a rotating single disk is numerically investigated. The finite volume method is used for solving the momentum equations. The numerical model and results are validated by comparing it to previously reported experimental data for velocities, angles and moment coefficients. It is demonstrated that increasing the axial distance increases the value of axial velocity and vice versa for tangential and total velocities. However, the maximum value of nondimensional radial velocity occurs near the disk wall. It is also found that with increase rotational Reynolds number, moment coefficient decreases.

Keywords: Rotating disk, Laminar flow, Numerical, Momentum

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Authors: A.Sankara Subramanian, G.Gurusamy, G.Selvakumar, P.Gnanasekar, A.Nagappan

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This paper presents an algorithm based on the wavelet decomposition, for feature extraction from the ECG signal and recognition of three types of Ventricular Arrhythmias using neural networks. A set of Discrete Wavelet Transform (DWT) coefficients, which contain the maximum information about the arrhythmias, is selected from the wavelet decomposition. After that a novel clustering algorithm based on nature inspired algorithm (Ant Colony Optimization) is developed for classifying arrhythmia types. The algorithm is applied on the ECG registrations from the MIT-BIH arrhythmia and malignant ventricular arrhythmia databases. We applied Daubechies 4 wavelet in our algorithm. The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.

Keywords: Daubechies 4 Wavelet, ECG, Nature inspired algorithm, Ventricular Arrhythmias, Wavelet Decomposition.

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Authors: Jurij Tasinkiewicz

Abstract:

The aim of this work is to present a theoretical analysis of a 2D ultrasound transducer comprised of crossed arrays of metal strips placed on both sides of thin piezoelectric layer (a). Such a structure is capable of electronic beam-steering of generated wavebeam both in elevation and azimuth. In this paper a semi-analytical model of the considered transducer is developed. It is based on generalization of the well-known BIS-expansion method. Specifically, applying the electrostatic approximation, the electric field components on the surface of the layer are expanded into fast converging series of double periodic spatial harmonics with corresponding amplitudes represented by the properly chosen Legendre polynomials. The problem is reduced to numerical solving of certain system of linear equations for unknown expansion coefficients.

Keywords: Beamforming, transducer array, BIS-expansion.

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Authors: Al-Amin Bhuiyan, Chang Hong Liu

Abstract:

Gabor-based face representation has achieved enormous success in face recognition. This paper addresses a novel algorithm for face recognition using neural networks trained by Gabor features. The system is commenced on convolving a face image with a series of Gabor filter coefficients at different scales and orientations. Two novel contributions of this paper are: scaling of rms contrast and introduction of fuzzily skewed filter. The neural network employed for face recognition is based on the multilayer perceptron (MLP) architecture with backpropagation algorithm and incorporates the convolution filter response of Gabor jet. The effectiveness of the algorithm has been justified over a face database with images captured at different illumination conditions.

Keywords: Fuzzily skewed filter, Gabor filter, rms contrast, neural network.

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

Abstract:

Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The MP is based on making the product of the speech wavelet transform coefficients (WTC). We have estimated our method on the Keele database. The results show the effectiveness of our method. It indicates that the two features can find word boundaries, and extracted the segments of the clean speech.

Keywords: Speech segmentation, Multi-scale product, Spectral centroid, Zero crossings rate.

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Authors: Nebi Gedik

Abstract:

The goal of motor image brain computer interface research is to create a link between the central nervous system and a computer or device. The most important signal for brain-computer interface is the electroencephalogram. The aim of this research is to explore a set of effective features from EEG signals, separated into frequency bands, using wave atom sub-bands to discriminate right and left-hand motor imagery signals. Over the transform coefficients, feature vectors are constructed for each frequency range and each transform sub-band, and their classification performances are tested. The method is validated using EEG signals from the BCI competition III dataset IIIa and classifiers such as support vector machine and k-nearest neighbors.

Keywords: motor imagery, EEG, Wave atom transform sub-bands, SVM, k-NN

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Authors: Yun-Yao Chi, Chieh-Kai Tsai, Dai-Ling Li

Abstract:

In this paper, a method of fast 3D topography modeling using the high-resolution camera images is studied based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D) urban landscape modeling. Firstly, the existing high-resolution digital camera with special design of overlap images is designed by reconstructing and analyzing the auto-flying paths of UAVs, which improves the self-calibration function to achieve the high precision imaging by software, and further increased the resolution of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of urban land surfaces and the texture extraction. Finally, the aerial photography and 3D topography construction are both developed in campus of Chang-Jung University and in Guerin district area in Tainan, Taiwan, provide authentication model for construction of 3D topography based on combined UAV-based camera images from system. The results demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D topography production, and the technology solution in this paper offers a new, fast, and technical plan for the 3D expression of the city landscape, fine modeling and visualization.

Keywords: 3D, topography, UAV, images.

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Authors: Rawaa H. El-Bidweihy, Hisham M. Abdelsalam, Ihab A. El-Khodary

Abstract:

In an era where machines run and shape our world, the need for a stable, non-ending source of energy emerges. In this study, the focus was on the solar energy in Egypt as a renewable source, the most important factors that could affect the solar energy’s market share throughout its life cycle production were analyzed and filtered, the relationships between them were derived before structuring a Bayesian network. Also, forecasted models were built for multiple factors to predict the states in Egypt by 2035, based on historical data and patterns, to be used as the nodes’ states in the network. 37 factors were found to might have an impact on the use of solar energy and then were deducted to 12 factors that were chosen to be the most effective to the solar energy’s life cycle in Egypt, based on surveying experts and data analysis, some of the factors were found to be recurring in multiple stages. The presented Bayesian network could be used later for scenario and decision analysis of using solar energy in Egypt, as a stable renewable source for generating any type of energy needed.

Keywords: ARIMA, auto correlation, Bayesian network, forecasting models, life cycle, partial correlation, renewable energy, SARIMA, solar energy.

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Authors: D. Bala Bhaskar

Abstract:

An algorithm is proposed for the order reduction of large scale linear dynamic multi variable systems where the reduced order model denominator is obtained by using Stability equation method and numerator coefficients are obtained by using SRAM. The proposed algorithm produces a lower order model for an original stable high order multivariable system. The reduction procedure is easy to understand, efficient and computer oriented. To highlight the advantages of the approach, the algorithm is illustrated with the help of a numerical example and the results are compared with the other existing techniques in literature.

Keywords: Multi variable systems, order reduction, stability equation method, SRAM, time domain characteristics, ISE.

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Authors: Mahmood M. Al-Imam, M. Mustafa

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In this paper, we present an experimental testing for a new algorithm that determines an optimal controller-s coefficients for output variance reduction related to Linear Time Invariant (LTI) Systems. The algorithm features simplicity in calculation, generalization to minimal and non-minimal phase systems, and could be configured to achieve reference tracking as well as variance reduction after compromising with the output variance. An experiment of DCmotor velocity control demonstrates the application of this new algorithm in designing the controller. The results show that the controller achieves minimum variance and reference tracking for a preset velocity reference relying on an identified model of the motor.

Keywords: Output variance, minimum variance, overparameterization, DC-Motor.

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Authors: Toshinori Nawata

Abstract:

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) using the automatic choosing functions of gradient optimization type for nonlinear systems. Constant terms which arise from sectionwise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics. Parameters included in the control are suboptimally selected by minimizing the Hamiltonian with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Keywords: augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.

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